Do Political Connections Buffer Firms from or Bind Firms to the Government? A Study of Corporate Charitable Donations of Chinese Firms

Do political connections buffer firms from or bind firms to the government? To examine this theoretical puzzle, we distinguish two types of managerial political connections, ascribed and achieved, and theorize that these different types of ties either buffer firms from or bind firms to government demands. Furthermore, we propose that these effects are contingent on both industrial and regional institutional conditions. We test our framework with a unique panel data set of privately controlled listed firms’ charitable donations in China from 2001 to 2012. We find that firms whose executives have ascribed bureaucratic connections are more likely to use their connections as a buffer from governmental donation pressure, particularly in competitive industries and less market-oriented regions, whereas in state-monopolized industries this buffering effect is reduced. In contrast, achieved political connections are more likely to serve a binding function that facilitates donation, particularly in state-monopolized industries and more market-oriented regions, but in less market oriented regions, they buffer firms from the pressure to donate. Our research contributes to the literatures on the effects of political connections, the institutional contingencies of political connections, and the relationship between corporate social responsibility (CSR) and corporate political activities (CPA)

Dynamic Simulation of Deposition Processes of Spacecraft Molecular Contamination

Accurate simulation and calculation of the deposition of outgassing molecule can shorten the cycle and reduce the cost of vacuum tests on satellites. It also provides a reference for contamination protection design by systems engineers. In this study, the molecular outgassing, transport and deposition processes were simulated by diffusion theory, the angle coefficient method, and the first-order desorption equation, respectively. The simulation results were consistent with the test data trends, but deviated from the test values. Given the effect of initial molecular outgassing rate, diffusion coefficient and residence time on the deposition mass, it was surmised that considering the molecular species and the weight mass rate would improve the calculation result. These considerations indeed improved the numerical simulations of high-vacuum contamination

Prediction and Characterization of Missing Proteomic Data in Desulfovibrio vulgaris

Proteomic datasets are often incomplete due to identification range and sensitivity issues. It becomes important to develop methodologies to estimate missing proteomic data, allowing better interpretation of proteomic datasets and metabolic mechanisms underlying complex biological systems. In this study, we applied an artificial neural network to approximate the relationships between cognate transcriptomic and proteomic datasets of Desulfovibrio vulgaris, and to predict protein abundance for the proteins not experimentally detected, based on several relevant predictors, such as mRNA abundance, cellular role and triple codon counts. The results showed that the coefficients of determination for the trained neural network models ranged from 0.47 to 0.68, providing better modeling than several previous regression models. The validity of the trained neural network model was evaluated using biological information (i.e. operons). To seek understanding of mechanisms causing missing proteomic data, we used a multivariate logistic regression analysis and the result suggested that some key factors, such as protein instability index, aliphatic index, mRNA abundance, effective number of codons (Nc) and codon adaptation index (CAI) values may be ascribed to whether a given expressed protein can be detected. In addition, we demonstrated that biological interpretation can be improved by use of imputed proteomic datasets

Circular RNA Expression Profile and Analysis of Their Potential Function in Psoriasis

Background/Aims: Circular RNAs (circRNAs) are evolutionary conserved circular non-coding RNAs that play a role in several diseases by sequestering (sponging) microRNAs (miRNAs). However, their role in psoriasis remains unclear. In the present study, we investigated the expression of circRNAs and analyzed their potential functions in psoriasis. Methods: The SBC human ceRNA array V1.0 was used to analyze circRNA expression in psoriatic lesions and normal healthy skin tissues. Functional analyses were performed using Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Putative miRNA response elements (MREs) were identified using miRNA target prediction software. Six upregulated circRNAs were verified by quantitative real-time reverse transcription polymerase chain reaction in psoriatic lesions and healthy skin tissues. Results: A total of 4956 circRNAs (3016 upregulated and 1940 downregulated; fold change ≥2 and p< 0.05) were identified as differentially expressed in psoriasis. Furthermore, 4405 MREs were identified among the differentially expressed circRNAs. hsa_circ_0061012 was upregulated in psoriatic lesions compared with normal healthy skin tissues. The top five MREs of hsa_circ_0061012 were hsa-miR-7157-5p, hsa-miR-4769-3p, hsa-miR-6817-5p, hsa-miR-4310, and hsa-miR-6882-3p. GO analysis was carried out to investigate the biological functions enriched among the upregulated targets of five miRNAs in psoriasis. The GO analysis identified that most of top 30 of GO enrichment are related to psoriasis. Conclusion: hsa_circ_0061012 might be a candidate biomarker for psoriasis. The results provide a new perspective for a better understanding of ceRNA-mediated gene regulation in psoriasis, and provide a novel theoretical basis for further studies on the function of circRNA in psoriasis

Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs) though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200 Homo sapiens targets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network

Case report: A de novo Non-sense SOX9 mutation (p.Q417*) located in transactivation domain is Responsible for Campomelic Dysplasia

BackgroundCampomelic dysplasia (CD) is an autosomal dominant skeletal dysplasia syndrome characterized by shortness and bowing of lower extremities, and often accompanied by XY sex reversal. Heterozygous pathogenic variants of SOX9 or rearrangement involving the long arm of chromosome 17 are the causes of disease. However, evidence for pathogenesis of SOX9 haploinsufficiency is insufficient.MethodsWe enrolled a Chinese family where the fetus was diagnosed with CD. The affected fetus was selected for whole-exome sequencing to identify the pathogenic mutations in this family.ResultsAfter data filtering, a novel non-sense SOX9 variant (NM_000346.3; c.1249C > T; p.Q417*) was identified as the pathogenic lesion in the fetus. Further co-segregation analysis using Sanger sequencing confirmed that this novel SOX9 mutation (c.1249C > T; p.Q417*) was a de novo mutation in the affected fetus. This terminated codon mutation identified by bioinformatics was located at an evolutionarily conserved site of SOX9. The bioinformatics-based analysis predicted this variant was pathogenic and affected SOX9 transactivation activity.ConclusionCD is a rare condition, which connected with SOX9 tightly. We identified a novel heterozygous SOX9 variant (p.Q417*) in a Chinese CD family. Our study supports the putative reduced transactivation of SOX9 variants in the pathogenicity of CD

Epigenetic control of translation checkpoint and tumor progression via RUVBL1-EEF1A1 axis

Epigenetic dysregulation is reported in multiple cancers including Ewing sarcoma (EwS). However, the epigenetic networks underlying the maintenance of oncogenic signaling and therapeutic response remain unclear. Using a series of epigenetics- and complex-focused CRISPR screens, RUVBL1, the ATPase component of NuA4 histone acetyltransferase complex, is identified to be essential for EwS tumor progression. Suppression of RUVBL1 leads to attenuated tumor growth, loss of histone H4 acetylation, and ablated MYC signaling. Mechanistically, RUVBL1 controls MYC chromatin binding and modulates the MYC-driven EEF1A1 expression and thus protein synthesis. High-density CRISPR gene body scan pinpoints the critical MYC interacting residue in RUVBL1. Finally, this study reveals the synergism between RUVBL1 suppression and pharmacological inhibition of MYC in EwS xenografts and patient-derived samples. These results indicate that the dynamic interplay between chromatin remodelers, oncogenic transcription factors, and protein translation machinery can provide novel opportunities for combination cancer therapy.</p